**Is there an easy way to obtain the covariance of the parameters from a constrained regression fit?**

I am using the PCLS function in the MGCV package in R to fit the constrained regression, however I am open to other approaches.

The constraint I am imposing is that the coefficients must be positive.

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#### Best Answer

At first I would go with very simple bootstrap.

Basically something as follows:

- Create a new data-set by resampling pairs of $(x,y)$.
- Run your regression on this new data set and you will get some parameters $hat beta$.
- Repeat 1 and 2 as many times as possible. Now you will have a large sets of $ hat beta$
- Now just take the sample covariance of your $hat beta$.
- Done

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